Do you really understand the concept of edge computing in the Internet of Things?

Blockchain nouns can be found on the street and become a hot new word. There are still few people talking about edge computing. Edge computing is more tangible to our life and work than blockchain. It has a broader market prospect and is a business area that must be considered in the 5G era and the Internet of Things era. As a friend interested in the communications industry, the Internet industry, and the IT industry, you must not miss the wave of edge computing. Below the old paste to sort out relevant information, take you 5 minutes to understand the edge calculation.

At the time of the rise of cloud computing, there was a view that the terminal only needs one display screen, and all the data of the Internet of Things is transmitted to the cloud center, and the cloud completes the operation process and then transmits it back to the user terminal. Therefore, thin terminals will be the future trend.

The reality is that the transition depends on the cloud center, which will cause the efficiency of the Internet of Things to fall short of expectations. Especially for scenarios with strict delay requirements, IoT deployment becomes meaningless. For example, in a scenario for security monitoring, the camera acquires user video and transmits it to the cloud center for processing. It requires not only high-speed bandwidth to transmit a large amount of invalid data, but also imposes a huge burden on the cloud center. The end result is high processing costs, long processing events, and inefficiency.

How to solve this problem? So the researchers modified the camera to keep the camera connected to the cloud center, but also have video processing, storage and recognition capabilities. The cloud center sends a comparison model to the camera, and the captured video will be processed and processed in real time on the camera side. The first time the information after the initial screening is transmitted to the cloud for high-precision recognition.

In this mode, the data captured by the camera can be processed in milliseconds, and the monitoring task is completed in the first time. We have made IoT terminals with intelligent processing capabilities an edge computing product.

The definition of “edge computing” in the industry refers to the open platform that integrates network, computing, storage and application core capabilities on the edge of the network close to the object or data source, and provides edge intelligent services nearby.

Intelligent network edge will become an important development direction in the future. With the construction of 5G networks, the Internet of Things has become one of the key networks. The industry expects that there will be more than 50 billion terminals and devices connected by 2020, and China alone will generate more than 10 billion IoT connections. All walks of life want to deploy the Internet of Things to provide customers with smarter and more convenient products and services. Edge computing has become the inevitable development direction of IoT terminals because of its agile, real-time, intelligent, and security features.

Edge computing has received a lot of attention in the industry. In 2016, the Edge Computing Industry Alliance was established. It was initiated by Huawei, Chinese Academy of Sciences, China Institute of Information and Communications, Intel, ARM and iSoftStone. By 2018, according to the list of affiliate websites, there are nearly 200. The member units of the family include 360, ABB, Aopu and other well-known enterprises from all walks of life.

There are three types of edge scenarios to consider when deploying edge services. They are the personal edge, the business edge, and the cloud edge.

(1) Personal edge

Personal edge computing revolves around us, sometimes at our side, right in our homes; for example, smartphones, home robots, smart glasses, medical sensors, wearable watches, smart speakers, and other home automation systems.

Personal edge devices are generally mobile and need to consider the characteristics of endurance, network switching and offline conditions.

(2) Business edge

The business edge is used to aggregate information about personal edge devices, and information such as robots and sensing devices are collected and processed here. Such devices can be deployed in office areas or home areas to support information concentration, interaction, and processing within the area.

(3) Cloud edge

A complex IoT application will involve the collaboration of multiple cloud platforms. The rise of vertical cloud platforms such as voice processing, face recognition, and medical artificial intelligence has improved the intelligence of the Internet of Things, but there is also a higher demand for collaboration between platforms. Cloud edge is equivalent to providing data parsing, data interaction, and data collaboration on different cloud platforms.

As one of the key technologies of 5G evolution, MEC can deploy functions such as computing, storage, offload, and big data analysis in the vicinity of the wireless edge network to implement localized distributed processing of carrier services, improve network data processing efficiency, and accelerate various networks. The rapid download of content, services and applications meets the ultimate experience of end users and meets the requirements of low industry delay, high traffic and security in vertical industry networks.

There are two main modes of support for edge computing in the 5G architecture. One is based on LADN to select edge UPF (user port); the other is that UPF can select services, and local services can choose to sink.

The three major operators have considered edge computing in the early stage of 5G deployment. The construction of business capabilities through edge networks can solve the problem of long-term coexistence of multiple networks in the 5G era.

Industry Alliance: Edge Computing Industry Alliance ECC (China), Edgecross Alliance (Japan), Avnu Alliance, etc.

Core research institutions: China Xintong Institute, Shenyang Institute of Automation, Chinese Academy of Sciences, Chongqing University of Posts and Telecommunications, etc., in enterprises, Microsoft, Siemens,.

Chip manufacturers: The main players of the chip have joined the edge computing industry. There are Huawei, Zhongtianwei, etc., as well as the newly created OURS; Intel and ARM are abroad.

Finished equipment manufacturers: manufacturers in all fields of the Internet, such as IoT switches, Internet of Things TV, IoT power equipment, etc.

Operator: China Mobile has launched a variety of MEC application pilots in more than 20 cities in 10 provinces; China Telecom and CDN companies want to deploy MEC edge CDN as an extension of existing CDNs, and at the same time Network user service;

Solution companies: Various ICT solution companies that integrate upstream resources to provide professional services to customers.

Edge computing will have direct application in the following six categories of industries. As the technology matures, it will extend to more industries in the future.

Local video services: sports events, concerts, museums, exhibition venues AR live and VR experience;

Industrial Internet: smart factories, intelligent production, intelligent equipment, intelligent machines, intelligent logistics, etc.;

Drone VR: no dead angle video live, 360-degree video backtracking, online VR live broadcast;

Vehicle networking applications: vehicle safety management, vehicle driving safety and urban traffic congestion management;

Artificial intelligence: electronic fence, face recognition, expression recognition, hotspot management, etc.

Mobile office: user access control, enterprise personalization, enterprise business control.